Embedded Files
Hirokazu Shirado is an Assistant Professor of the Human-Computer Interaction Institute in the School of Computer Science at Carnegie Mellon University. He obtained his doctorate in Sociology at Yale University in 2019, where he was a member of the Human Nature Lab at the Yale Institute for Network Science. Before Yale, he spent eight years as an engineering researcher at Sony Corporation.
His research focuses on the role of social interactions and technology in the emergence of social order and in the collective confrontation of social dilemmas. He is particularly committed to the experimental study of cooperative behaviors as they manifest through interactions between people within social networks. He is also studying hybrid systems of humans and machines, particularly how machine intelligence can help people address collective action challenges.
Individual and Collective Learning in Experimental Social Networks Facing "Danger"
Individual and Collective Learning in Experimental Social Networks Facing "Danger"
While social networks jeopardize people’s well-being by working as diffusion pathways of falsehood, they may also help people overcome the challenge of misinformation with time and experience. In this talk, I discuss how social networks can provide learning facilitation using an experiment involving an iterated decision-making game simulating an unpredictable situation faced by a group (N = 2786 subjects in 120 groups). In the experiment, social networks initially spread false information and suppressed necessary actions, known as normalcy bias. However, with tie rewiring, social networks facilitated improvement in collective intelligence as people accumulated experiences. It also shows that the network’s learning facilitation resulted from integrating individual experiences into structural changes. Finally, I touch on an ongoing project to address several challenges of social networks found through the experiment.
Report abuse